Influence of converting forestland to tea plantation on soil preferential flow occurrence in subtropical hillslopes of Three Gorges Reservoir Area, China by Jiapan Xu, Xue Shen, Muxing Liu, Jun Zhang, Qian Yang, Jun Yi, Shenglong Li, Chongfa Cai

Get full text

Climate change adaptation strategy of Greco grapevine by Antonello Bonfante, Maurizio Buonanno, Andrea Vitale, Arturo Erbaggio, Chiara Cirillo, Eleonora Guadagno, Francesca Petracca, Chiara Amitrano, Filippo Accomando, Angelita Gambuti, Veronica De Micco

Get full text

Adaptive Management Based on the Habitat Change of Cibotium barometz Under Synergistic Impact of Climate and Land Use Change—A Case Study of Guangxi, China by Bin Feng, Yunyun Zhang, Yunfeng Huang, Huabing Dai, Chao Yang, Chengling Yang, Kedao Lai

“…The areas of cropland, forest, shrub, grassland, and barren that meet C. barometz's survival requirements are decreasing, and water and impervious surfaces are increasing. …”
Get full text

Ecological Modelling of Farmland Transition: Food Web Dynamics and Multi-Objective Agricultural Optimization by Hao Rongrong, Wang Jinghan, Deng Zihui, Liu Tao

“…This study presents an integrated modelling framework combining ecological dynamics and agricultural decision-making to address challenges arising from forest-to-farmland conversion. A food web dynamics model simulates the energy flow and population changes across trophic levels under the influence of seasonal agricultural cycles and chemical inputs. …”
Get full text

Enhancing Network Security: A Study on Classification Models for Intrusion Detection Systems by Abeer Abd Alhameed Mahmood, Azhar A. Hadi, Wasan Hashim Al-Masoody

“…Multiclass classification presents challenges with identifying minor classes, but performance improves with additional hidden layers. Random Forest outperforms other classifiers in accuracy, which is consistent with simulation results.…”
Get full text

STATUS EKOSISTEM PESISIR BAGI PERENCANAAN TATA RUANG WILAYAH PESISIR DI KAWASAN TELUK AMBON by YULIA Asyiawati, FREDINAN YULIANDA, ROKHMIN DAHURI, SANTUN R.P. SITORUS, SETYO BUDI SUSILO

“…Ecosystem conditions in Ambon Bay Area is affected by land use on land, namely forest area and population. Refferral of land use planning in Ambon Bay Areas wich recommended in this study for a period of 20 years of protected areas and cultivated areas. …”
Get full text

Analysis and Prediction of Spatial and Temporal Land Use Changes in the Urban Agglomeration on the Northern Slopes of the Tianshan Mountains by Xiaoxu He, Zhaojin Yan, Yicong Shi, Zhe Wei, Zhijie Liu, Rong He

“…Using land use data, we analyzed transitions, dynamics, intensity, and gravity shifts in land use, examined driving mechanisms using geographic detectors, and simulated future land use patterns with the Patch-generating Land Use Simulation (PLUS) model. …”
Get full text

Machine learning-driven insights into phase prediction for high entropy alloys by Reliance Jain, Sandeep Jain, Sheetal Kumar Dewangan, Lokesh Kumar Boriwal, Sumanta Samal

“…The ML models such as multi layer precreptron MLP, Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), KNN, XGB nad SVM Classifier algorithm were used for the identifying the phase of HEAs. …”
Get full text

Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…The detection abilities of ensemble models are enhanced by integrating the strengths of the Random Forest algorithm (RFA), which safeguards against intricate dangers. …”
Get full text

Global biome changes over the last 21 000 years inferred from model–data comparisons by C. Li, C. Li, A. Dallmeyer, J. Ni, M. Chevalier, M. Willeit, A. A. Andreev, X. Cao, L. Schild, L. Schild, B. Heim, M. Wieczorek, U. Herzschuh, U. Herzschuh, U. Herzschuh

“…Specifically, they reveal a global shift from open glacial non-forest megabiomes to Holocene forest megabiomes since the Last Glacial Maximum (LGM), in line with the general climate warming trend and continental ice-sheet retreat. …”
Get full text

Spatiotemporal evolution and influencing factors of carbon stock in the water receiving areas from the perspective of carbon neutrality by Zhuoyue Peng, Mengting Li, Yaming Liu, Junxian Yin, Hongyuan Fang, Jiawei Wen

“…Based on multi-scenario simulation, under the ER-SNWDP scenario, built-up land expansion would be curbed, forest and grassland reductions would be alleviated, and water areas would increase significantly compared to the natural variation scenario. (2) Due to the implementation of the project, the research area had better carbon sequestration capacity. …”
Get full text

An Ecological Risk Assessment of the Dianchi Basin Based on Multi-Scenario Land Use Change Under the Constraint of an Ecological Defense Zone by Shu Wang, Quanli Xu, Junhua Yi, Qinghong Wang, Qihong Ren, Youyou Li, Zhenheng Gao, You Li, Huishan Wu

“…Therefore, we selected the Dianchi basin as the study area, extracted the ecological defense zone as the restricted conversion zone, and used the PLUS (Patch-generating Land Use Simulation) model to simulate land use for 2030 under multiple scenarios. …”
Get full text

The Pollen Representation of Vegetation and Climate Along an Altitudinal Gradient on the Eastern Tibetan Plateau by Weihe Ren, Min Liu, Feng Qin, Quan Li, Guitian Yi, Weiyu Chen, Shuming Li, Zijian Liu, Qing Peng, Chen Liang, Yan Zhao

Get full text

An ecosystem resilience index that integrates measures of vegetation function, structure, and composition by Marie Johnson, Ashley Ballantyne, Jon Graham, Zachary Holden, Zachary Hoylman, Kelsey Jensco, David Ketchum, John Kimball, Jessica Mitchell

Get full text

A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset by Ghadeer Jasim Mahdi

“…SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. …”
Get full text

Movie Box Office Prediction Based on IFOA-GRNN by Wei Lu, Xiaoqiao Zhang, Xinchen Zhan

“…By comparing this model with FOA-GRNN, KNN, GRNN, Random Forest, Naive Bayes, Ensembles for Boosting, Discriminant Analysis Classifier, and SVM, it is found that the prediction effect of the IFOA-GRNN model is significantly better than the above eight models. …”
Get full text

Used economy market insight: Sailboat industry pricing mechanism and regional effects. by Zhanni Huang, Hansheng Hu, Di Wu

“…Therefore, this article uses the random forest model and XGBoost algorithm to identify core price indicators, and uses an innovative rolling NAR dynamic neural network model to simulate and predict second-hand sailboat price data. …”
Get full text

Routing in Duty-Cycled Surveillance Sensor Networks by Zhong Shen, Peng Zhang

“…In surveillance applications (e.g., forest fire alarm or intruder detection), it is desired to report detected events to the sink node as soon as possible. …”
Get full text

QoS and Energy Aware Cooperative Routing Protocol for Wildfire Monitoring Wireless Sensor Networks by Mohamed Maalej, Sofiane Cherif, Hichem Besbes

“…However, this application requires a design of WSN taking into account the network lifetime and the shadowing effect generated by the trees in the forest environment. Cooperative communication is a promising solution for WSN which uses, at each hop, the resources of multiple nodes to transmit its data. …”
Get full text

Centrality nearest-neighbor projected-distance regression (C-NPDR) feature selection for correlation-based predictors with application to resting-state fMRI study of major depressi... by Elizabeth Kresock, Bryan Dawkins, Henry Luttbeg, Yijie Jamie Li, Rayus Kuplicki, B A McKinney

“…Centrality-based NPDR can be coupled with any centrality method and can be coupled with importance scores other than NPDR, such as random forest importance scores. We develop a new simulation method using random network theory to generate artificial correlation data predictors with variations in correlations that affect class prediction.…”
Get full text